Knowledge catalogue
Bank of England governor Andrew Bailey today warned that advanced artificial intelligence poses risks to financial infrastructure. Bailey outlined his concerns in a letter to G20 finance ministers and
arXiv:2608.29553v1 Announce Type: new Abstract: Geospatial foundation models such as the AlphaEarth Foundation produce compact and globally consistent representations of the Earth's surface that trans
arXiv:2608.30866v1 Announce Type: new Abstract: Building language technologies and conducting NLP research for low-resource languages---particularly when led by native speakers or involving participat
arXiv:2608.30333v1 Announce Type: cross Abstract: Next-basket repurchase recommendation is commonly formulated as a ranking task: given a customer's purchase history, the system ranks previously purch
arXiv:2608.30731v1 Announce Type: cross Abstract: Assessing claim check-worthiness is an essential first step in automated fact-checking pipelines. This work is motivated by a real deployment challeng
arXiv:2608.30342v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) enables photorealistic real-time novel view synthesis, yet placing a virtual camera to capture a desired frame remains larg
arXiv:2608.30352v1 Announce Type: new Abstract: Clinical AI often optimizes predictive performance without engaging how clinicians decide where to look and what to write. We present Co-Annotator, whic
arXiv:2608.28909v1 Announce Type: new Abstract: Large-scale, publicly available datasets have driven advances in deep learning, but privacy and legal restrictions often limit data sharing in medical i
arXiv:2608.29430v1 Announce Type: cross Abstract: Industrial recommenders give new content initial views through budgeted exploration, then use early performance to decide further delivery. On many sh
arXiv:2509.04859v4 Announce Type: replace Abstract: Fast and efficient photorealistic 3D reconstruction with (semantic) Gaussian Splatting (GS) is crucial for time-critical robotic perception and navi
arXiv:2608.28645v1 Announce Type: cross Abstract: Low-resource languages without an adequate training corpus often use a related, higher-resource language as a scaffold for comprehension. Still, there
arXiv:2608.29243v1 Announce Type: new Abstract: Existing diffusion-based enhancement methods provide strong generative capability for low-light image enhancement (LLIE), yet they either rely on paired
arXiv:2608.29966v1 Announce Type: new Abstract: Domain adaptation of large language models increasingly depends on constructing high-quality training data, yet existing data-preparation pipelines typi
arXiv:2306.11313v5 Announce Type: replace-cross Abstract: Point process models are widely used for continuous-time discrete-event data, where each data point includes time and additional information c
arXiv:2608.29925v1 Announce Type: new Abstract: Controllable image relighting is an important problem in image editing, and hand-drawn scribbles provide an intuitive interface for specifying the desir
arXiv:2608.30163v1 Announce Type: cross Abstract: Real-world knowledge resides in multimodal documents, necessitating retrieval-augmented generation (RAG) for accurate question answering. However, exi
arXiv:2608.28630v1 Announce Type: cross Abstract: Compared with half-duplex dialogue systems where the system waits for user turn completion before it responds, natural full-duplex dialogue systems re
arXiv:2608.29110v1 Announce Type: new Abstract: The United States has allocated approximately $65 billion through the Infrastructure Investment and Jobs Act for broadband expansion, yet evidence-based
arXiv:2608.30690v1 Announce Type: new Abstract: Visual SLAM is commonly evaluated on clean trajectories, although deployment failures are often caused by adverse weather, illumination, blur, and senso
arXiv:2601.10015v2 Announce Type: replace Abstract: Personalized Federated Learning (PFL) excels at tailoring client-specific models, which is particularly critical for decentralized and heterogeneous
Introduction Beginning in 2024 Mandiant investigated a string of compromises affecting Brazilian financial services, retail, and eCommerce organizations. Google Threat Intelligence Group (GTIG) tracks
arXiv:2608.29336v1 Announce Type: new Abstract: FISICA is a body-assessment and recommendation service running in production. One standing session with two photographs returns foot-loading measures, p
arXiv:2608.30046v1 Announce Type: cross Abstract: Noisy labels remain a critical challenge for training deep neural networks, since memorizing incorrect labels degrades generalization. Once noisy samp
arXiv:2608.30392v1 Announce Type: new Abstract: Global food security and sustainable climate action increasingly rely on robust, scalable agricultural monitoring. Earth observation foundation models h
arXiv:2608.28973v1 Announce Type: cross Abstract: Philosophers and legal scholars are engaged in debates about the implications of artificial intelligence for freedom of expression. This paper analyze
arXiv:2608.30419v1 Announce Type: new Abstract: Healthcare workforce scheduling is an NP-hard optimization problem requiring simultaneous satisfaction of labor regulations, coverage requirements, empl
Gilbert + Tobin uses ChatGPT and Codex in governed legal operations; OpenAI reports 87% active usage among enabled users.
arXiv:2412.06210v3 Announce Type: replace Abstract: With the rapid development of the Internet of Things (IoT), federated learning (FL) has gained increasing attention for its privacy-preserving use o
Hugging Face is (also) the best place to write about AI. > Your articles are now automatically linked from your model pages, so anyone looking at the model finds what you wrote about it. > We shipped
arXiv:2603.26024v2 Announce Type: replace Abstract: Identification of causal directionality in bivariate numerical data is a fundamental research problem with important practical implications. This pa
arXiv:2608.29884v1 Announce Type: new Abstract: We show that sequence-level distillation from a capable long-context teacher model is a simple, annotation-free, and data-efficient strategy for improvi
arXiv:2608.31037v1 Announce Type: new Abstract: Neural audio codecs (NACs) convert speech into discrete token sequences, and prior work has reported that these sequences follow language-like statistic
arXiv:2608.28601v1 Announce Type: new Abstract: Interactive visualizations support conceptual understanding in undergraduate mathematics, but building them has required programming expertise most inst
arXiv:2608.30935v1 Announce Type: cross Abstract: Embodied navigation requires agents to translate heterogeneous goals and visual observations into actions across tasks, environments, and robot embodi
arXiv:2608.29640v1 Announce Type: cross Abstract: Large language models (LLMs) have shown promise for spatio-temporal forecasting, but existing approaches often rely on regularly sampled token sequenc
arXiv:2510.13387v3 Announce Type: replace Abstract: Large language models (LLMs) still struggle with strategic persuasion, largely because existing approaches either neglect information asymmetry or r
arXiv:2412.00241v3 Announce Type: replace Abstract: Edge-attributed multigraphs, in which multiple edges with distinct attributes connect the same pair of nodes, arise naturally in many real-world sys
arXiv:2608.30563v1 Announce Type: new Abstract: Multimodal Emotion Recognition (MER) systems often suffer from missing modalities in real-world scenarios. Existing methods usually generate, align, or
arXiv:2608.28886v1 Announce Type: cross Abstract: What does a generation loop gain from learning on its own verified successes? In cycles of generate, verify, select and LoRA-consolidate on online bin
arXiv:2505.23862v2 Announce Type: replace-cross Abstract: The mRNA optimization is essential for mRNA vaccines, therapies, and industrial protein production. Based on current explorations, an ideal op
arXiv:2608.28680v1 Announce Type: new Abstract: Informal settlements represent a major urban challenge in rapidly expanding cities, yet their identification from Earth Observation (EO) data remains di
arXiv:2608.30997v1 Announce Type: new Abstract: Reflective smartphone cover glass is challenging to inspect from a single fixed viewpoint because defect visibility varies with viewing geometry and spe
arXiv:2608.30662v1 Announce Type: new Abstract: This paper presents Murano, an open source framework for designing, running, and reproducing mechanistic interpretability studies of large language mode
arXiv:2608.30940v1 Announce Type: cross Abstract: Generative music systems are increasingly presented as tools that democratize music creation, yet their practical suitability for musicians remains un
arXiv:2512.23667v3 Announce Type: replace Abstract: Intrinsic image decomposition aims to recover material and illumination factors from RGB observations, but real-world images entangle reflectance wi
arXiv:2608.30738v1 Announce Type: new Abstract: Robust understanding of user input is a core requirement for voice assistants deployed in real-world environments. In practice, these systems encounter
arXiv:2608.29066v1 Announce Type: cross Abstract: Stance detection is crucial for understanding the underlying attitude of an expression towards a target. Conversational stance detection is a more cha
arXiv:2608.29905v1 Announce Type: new Abstract: Text-guided style editing of 3D assets is essential for adapting existing objects to diverse visual aesthetics in digital content creation. Despite rapi
arXiv:2608.29867v1 Announce Type: new Abstract: Autoencoders are widely used for nonlinear dimensionality reduction and manifold learning. While most common implementations rely on both nonlinear enco
arXiv:2608.30782v1 Announce Type: new Abstract: Real-world image super-resolution (Real-ISR) aims to preserve structures supported by the degraded observation while reconstructing perceptually realist
arXiv:2608.29356v1 Announce Type: new Abstract: Artificial Intelligence (AI) has long been inspired by studies of biological intelligence. Reinforcement learning, for instance, drew inspiration from s
arXiv:2509.10882v2 Announce Type: replace Abstract: In high-stakes domains such as healthcare, privacy concerns severely limit the use of real-world training data. Differentially private (DP) syntheti
arXiv:2608.28640v1 Announce Type: cross Abstract: In this paper, we present PromptKWS, a novel Prompt-guided keyword spotting (KWS) framework to improve the accuracy of open vocabulary KWS systems. In
arXiv:2608.28895v1 Announce Type: new Abstract: We introduce ReconSplat, a feed-forward model for 3D scene reconstruction that aims to address the longstanding trade-off between plausible view generat
arXiv:2608.29809v1 Announce Type: new Abstract: Real-world image generation often involves multi-turn editing, where users iteratively modify small regions while most image content remains unchanged.
arXiv:2608.29368v1 Announce Type: new Abstract: The most disruptive step that enterprises of small-medium size and maturity can take to make the most of the latest technological advances in AI is to s
arXiv:2608.30541v1 Announce Type: new Abstract: Pixel-based language models (LMs) replace traditional tokenizers by processing rendered images of text, making cross-lingual transfer heavily dependent
arXiv:2602.01419v2 Announce Type: replace-cross Abstract: High-level Computer-Aided Process Planning (CAPP) generates manufacturing process plans from part specifications. It suffers from limited data
arXiv:2608.29315v1 Announce Type: cross Abstract: This work introduces Semantically-Guided Exploration (SGE), a modular exploration framework for ground vehicles that integrates pixel-level semantic s
arXiv:2608.28600v1 Announce Type: new Abstract: Large language models (LLMs) achieve strong performance on mathematical reasoning benchmarks, yet the mathematically meaningful skills underlying their